This application relates generally to management of animal herds. More specifically, this application relates to management of animal herds using distributed sensor networks.
Modern livestock operations require sophisticated techniques to manage the livestock efficiently. In managing a herd of animals, which may be raised to provide meat, milk, or other commercial products, it is generally necessary to use techniques to monitor the status of the herd and of individual animals within the herd on an on-going basis. This is true for relatively simple functions, such as inventory functions, in which the location of each animal being raised is known and monitored, but is also true for more sophisticated functions. For example, modern livestock operations spend considerable effort to ensure that animal reproduction is performed between animals having desirable combinations of genetic characteristics. The coordination of such reproduction involves at least two components: first, it is necessary to maintain pedigree information for each animal so that the desired genetic characteristics can be tracked; second, it is necessary to identify reproductive cycles of female animals so that the timing of reproduction may be coordinated.
The current state of the art in livestock management is deficient in some respects. For example, some inventory functions currently use radio-frequency identification (“RFID”) tags that are affixed to an animal, often to the animals ear, and provide a signal that uniquely identifies the animal. To check the inventory, the animals are routed through a turnstile, allowing each RFID tag to be read by a reader local to the turnstile, with the identification being provided from the RFID tag being used to identify the particular animal from a database, and thereby verify its presence in the herd.
Such a technique requires human involvement in rounding up the animals and routing them through the turnstile. But perhaps even more significant is the fact that performing an inventory function in this way is very discrete, providing information only at the time the inventory check is made. Such discrete sampling is also evident in other aspects of current livestock management techniques, such as health monitoring. Current techniques periodically check the health of animals, but do not generally provide any simple way of identifying health issues as they occur, whether those health issues be negative issues like potential illnesses or positive issues like entering a state of estrus.
The need for improved real-time livestock management capabilities is thus felt in the art. In recent years, this need has become more acute as new diseases like bovine spongiform encephalitis have devastated cattle stocks. An ability to identify potential health issues early and to take remedial steps could mitigate the impact of this and other emerging diseases. Furthermore, there has recently been greater recognition that deliberate interference with animal stocks might be used by terrorist groups as a technique for interfering with food distribution. The increased recognition of a need in the art for improved real-time livestock management capabilities is also felt in this way.